numpy.polynomial.laguerre.lagder()
  • References/Python/NumPy/Routines/Polynomials/Polynomial Package/Laguerre Module

numpy.polynomial.laguerre.lagder(c, m=1, scl=1, axis=0)

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numpy.core.defchararray.index()
  • References/Python/NumPy/Routines/String operations

numpy.core.defchararray.index(a, sub, start=0, end=None)

2025-01-10 15:47:30
numpy.ma.ptp()
  • References/Python/NumPy/Routines/Masked array operations

numpy.ma.ptp(obj, axis=None, out=None, fill_value=None)

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numpy.lib.NumpyVersion()
  • References/Python/NumPy/Routines/Miscellaneous routines

class numpy.lib.NumpyVersion(vstring)

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numpy.array()
  • References/Python/NumPy/Routines/Array creation routines

numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0) Create an array.

2025-01-10 15:47:30
RandomState.rayleigh()
  • References/Python/NumPy/Routines/Random sampling

RandomState.rayleigh(scale=1.0, size=None) Draw samples from a Rayleigh distribution. The

2025-01-10 15:47:30
numpy.ma.shape()
  • References/Python/NumPy/Routines/Masked array operations

numpy.ma.shape(obj)

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numpy.sinh()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.sinh(x[, out]) = Hyperbolic sine, element-wise. Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) or -1j

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numpy.expm1()
  • References/Python/NumPy/Routines/Mathematical functions

numpy.expm1(x[, out]) = Calculate exp(x) - 1 for all elements in the array.

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numpy.vander()
  • References/Python/NumPy/Routines/Array creation routines

numpy.vander(x, N=None, increasing=False)

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